Name
Abstract | ||
|---|---|---|
Generating summaries that meet the information needs of a user relies on (1) several forms of question decomposition; (2) different summarization approaches; and (3) textual inference for combining the summarization strategies. This novel framework for summarization has the advantage of producing highly responsive summaries, as indicated by the evaluation results. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1016/j.ipm.2007.01.004 | Inf. Process. Manage. |
Keywords | Field | DocType |
summarization,satisfiability,textual entailment,information need | Multi-document summarization,Automatic summarization,Information needs,Question answering,Information retrieval,Textual entailment,Inference,Computer science,Artificial intelligence,Natural language processing | Journal |
Volume | Issue | ISSN |
43 | 6 | 0306-4573 |
Citations | PageRank | References |
21 | 1.16 | 16 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Sanda Harabagiu | 1 | 2203 | 221.65 |
| Andrew Hickl | 2 | 358 | 21.88 |
| Finley Lacatusu | 3 | 201 | 9.67 |